Indications for Submandibulectomy Within a 20-Year Period

Purpose: Different pathologies of the submandibular gland are an indication of submandibular gland excision-ranging from inflammatory causes and sialolithiasis to malignant tumors. The purpose of this study was to get an overview of the different indications for submandibular gland excision. Methods: The main goal of this study was to evaluate the different indications for submandibular gland excision during a 20-year period. In addition, epidemiological information and therapy concepts were investigated with a special focus on Tumor Lymph nodes Metastasis (TNM) classification and recurrence rate. Procedures during which the submandibular gland was removed while not being the primary cause for surgery (eg, neck dissection in Level Ib) were not included. Results: During the period of observation, 359 submandibular gland excisions were performed. The most common cause for submandibular gland excision was sialolithiasis (n = 129) with intraparenchymal stone localization. Up next were inflammatory causes (n = 115) in particular chronic submandibular sialadenitis followed by only a few cases of Sjögren's syndrome, sarcoidosis, and tuberculosis. In 115 cases, surgery was performed for tumors of the submandibular gland, with 88 of them being benign and 27 malignant. Malignancies were then divided into lymphomas (n = 9) and primary salivary gland malignancies (n = 18). Conclusion: This retrospective study of a large cohort of patients displays a representative overview of the indications for submandibular gland excision. Sialolithiasis was the most common underlying cause of gland excision. The malignancy rate in our cohort was lower than described in the literature.

Establishment of a Machine Learning Model for the Risk Assessment of Perineural Invasion in Head and Neck Squamous Cell Carcinoma

Perineural invasion is a prevalent pathological finding in head and neck squamous cell carcinoma and a risk factor for unfavorable survival. An adequate diagnosis of perineural invasion by pathologic examination is limited due to the availability of tumor samples from surgical resection, which can arise in cases of definitive nonsurgical treatment. To address this medical need, we established a random forest prediction model for the risk assessment of perineural invasion, including occult perineural invasion, and characterized distinct cellular and molecular features based on our new and extended classification. RNA sequencing data of head and neck squamous cell carcinoma from The Cancer Genome Atlas were used as a training cohort to identify differentially expressed genes that are associated with perineural invasion. A random forest classification model was established based on these differentially expressed genes and was validated by inspection of H&E-stained whole image slides. Differences in epigenetic regulation and the mutational landscape were detected by an integrative analysis of multiomics data and single-cell RNA-sequencing data were analyzed. We identified a 44-gene expression signature related to perineural invasion and enriched for genes mainly expressed in cancer cells according to single-cell RNA-sequencing data. A machine learning model was trained based on the expression pattern of the 44-gene set with the unique feature to predict occult perineural invasion. This extended classification model enabled a more accurate analysis of alterations in the mutational landscape and epigenetic regulation by DNA methylation as well as quantitative and qualitative differences in the cellular composition in the tumor microenvironment between head and neck squamous cell carcinoma with or without perineural invasion. In conclusion, the newly established model could not only complement histopathologic examination as an additional diagnostic tool but also guide the identification of new drug targets for therapeutic intervention in future clinical trials with head and neck squamous cell carcinoma patients at a higher risk for treatment failure due to perineural invasion.

A Novel Subgroup of UCHL1-Related Cancers Is Associated with Genomic Instability and Sensitivity to DNA-Damaging Treatment

PURPOSE

Identification of molecularly-defined cancer subgroups and targeting tumor-specific vulnerabilities have a strong potential to improve treatment response and patient outcomes but remain an unmet challenge of high clinical relevance, especially in head and neck squamous cell carcinoma (HNSC).

EXPERIMENTAL DESIGN

We established a UCHL1-related gene set to identify and molecularly characterize a UCHL1-related subgroup within TCGA-HNSC by integrative analysis of multi-omics data. An extreme gradient boosting model was trained on TCGA-HNSC based on GSVA scores for gene sets of the MSigDB to robustly predict UCHL1-related cancers in other solid tumors and cancer cell lines derived thereof. Potential vulnerabilities of UCHL1-related cancer cells were elucidated by an in-silico drug screening approach.

RESULTS

We established a 497-gene set, which stratified the TCGA-HNSC cohort into distinct subgroups with a UCHL1-related or other phenotype. UCHL1-related HNSC were characterized by higher frequencies of genomic alterations, which was also evident for UCHL1-related cancers of other solid tumors predicted by the classification model. These data indicated an impaired maintenance of genomic integrity and vulnerability for DNA-damaging treatment, which was supported by a favorable prognosis of UCHL1-related tumors after radiotherapy, and a higher sensitivity of UCHL1-related cancer cells to irradiation or DNA-damaging compounds (e.g., Oxaliplatin).

CONCLUSION

Our study established UCHL1-related cancers as a novel subgroup across most solid tumor entities with a unique molecular phenotype and DNA-damaging treatment as a specific vulnerability, which requires further proof-of-concept in pre-clinical models and future clinical trials.